BUG: using loc[int] with object index (pandas-dev#31905)

* BUG: using loc[int] with object index

* whatsnew

Author: jbrockmendel

doc/source/whatsnew/v1.1.0.rst

@@ -56,6 +56,8 @@ Other API changes
 - :meth:`Series.describe` will now show distribution percentiles for ``datetime`` dtypes, statistics ``first`` and ``last``
   will now be ``min`` and ``max`` to match with numeric dtypes in :meth:`DataFrame.describe` (:issue:`30164`)
 - :meth:`Groupby.groups` now returns an abbreviated representation when called on large dataframes (:issue:`1135`)
+- ``loc`` lookups with an object-dtype :class:`Index` and an integer key will now raise ``KeyError`` instead of ``TypeError`` when key is missing (:issue:`31905`)
+-
 
 Backwards incompatible API changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -160,6 +162,8 @@ Indexing
 - Bug in :meth:`DatetimeIndex.get_loc` raising ``KeyError`` with converted-integer key instead of the user-passed key (:issue:`31425`)
 - Bug in :meth:`Series.xs` incorrectly returning ``Timestamp`` instead of ``datetime64`` in some object-dtype cases (:issue:`31630`)
 - Bug in :meth:`DataFrame.iat` incorrectly returning ``Timestamp`` instead of ``datetime`` in some object-dtype cases (:issue:`32809`)
+- Bug in :meth:`Series.loc` and :meth:`DataFrame.loc` when indexing with an integer key on a object-dtype :class:`Index` that is not all-integers (:issue:`31905`)
+-
 
 Missing
 ^^^^^^^

pandas/core/indexes/base.py

@@ -3111,7 +3111,7 @@ def _convert_scalar_indexer(self, key, kind: str_t):
                     self._invalid_indexer("label", key)
 
             elif kind == "loc" and is_integer(key):
-                if not self.holds_integer():
+                if not (is_integer_dtype(self.dtype) or is_object_dtype(self.dtype)):
                     self._invalid_indexer("label", key)
 
         return key

pandas/core/series.py

@@ -969,9 +969,11 @@ def _get_value(self, label, takeable: bool = False):
         if takeable:
             return self._values[label]
 
+        # Similar to Index.get_value, but we do not fall back to positional
+        loc = self.index.get_loc(label)
         # We assume that _convert_scalar_indexer has already been called,
         #  with kind="loc", if necessary, by the time we get here
-        return self.index.get_value(self, label)
+        return self.index._get_values_for_loc(self, loc, label)
 
     def __setitem__(self, key, value):
         key = com.apply_if_callable(key, self)

pandas/tests/indexing/test_categorical.py

@@ -82,11 +82,7 @@ def test_loc_scalar(self):
         with pytest.raises(TypeError, match=msg):
             df.loc["d", "C"] = 10
 
-        msg = (
-            "cannot do label indexing on CategoricalIndex with these "
-            r"indexers \[1\] of type int"
-        )
-        with pytest.raises(TypeError, match=msg):
+        with pytest.raises(KeyError, match="^1$"):
             df.loc[1]
 
     def test_getitem_scalar(self):

pandas/tests/indexing/test_loc.py

@@ -16,7 +16,7 @@ class TestLoc(Base):
     def test_loc_getitem_int(self):
 
         # int label
-        self.check_result("loc", 2, typs=["labels"], fails=TypeError)
+        self.check_result("loc", 2, typs=["labels"], fails=KeyError)
 
     def test_loc_getitem_label(self):
 
@@ -34,7 +34,7 @@ def test_loc_getitem_label_out_of_range(self):
         self.check_result(
             "loc", 20, typs=["ints", "uints", "mixed"], fails=KeyError,
         )
-        self.check_result("loc", 20, typs=["labels"], fails=TypeError)
+        self.check_result("loc", 20, typs=["labels"], fails=KeyError)
         self.check_result("loc", 20, typs=["ts"], axes=0, fails=TypeError)
         self.check_result("loc", 20, typs=["floats"], axes=0, fails=KeyError)
 
@@ -967,3 +967,11 @@ def test_loc_set_dataframe_multiindex():
     result = expected.copy()
     result.loc[0, [(0, 1)]] = result.loc[0, [(0, 1)]]
     tm.assert_frame_equal(result, expected)
+
+
+def test_loc_mixed_int_float():
+    # GH#19456
+    ser = pd.Series(range(2), pd.Index([1, 2.0], dtype=object))
+
+    result = ser.loc[1]
+    assert result == 0

pandas/tests/indexing/test_scalar.py

@@ -138,30 +138,22 @@ def test_series_at_raises_type_error(self):
         result = ser.loc["a"]
         assert result == 1
 
-        msg = (
-            "cannot do label indexing on Index "
-            r"with these indexers \[0\] of type int"
-        )
-        with pytest.raises(TypeError, match=msg):
+        with pytest.raises(KeyError, match="^0$"):
             ser.at[0]
-        with pytest.raises(TypeError, match=msg):
+        with pytest.raises(KeyError, match="^0$"):
             ser.loc[0]
 
-    def test_frame_raises_type_error(self):
+    def test_frame_raises_key_error(self):
         # GH#31724 .at should match .loc
         df = DataFrame({"A": [1, 2, 3]}, index=list("abc"))
         result = df.at["a", "A"]
         assert result == 1
         result = df.loc["a", "A"]
         assert result == 1
 
-        msg = (
-            "cannot do label indexing on Index "
-            r"with these indexers \[0\] of type int"
-        )
-        with pytest.raises(TypeError, match=msg):
+        with pytest.raises(KeyError, match="^0$"):
             df.at["a", 0]
-        with pytest.raises(TypeError, match=msg):
+        with pytest.raises(KeyError, match="^0$"):
             df.loc["a", 0]
 
     def test_series_at_raises_key_error(self):